| Debiased explainable pairwise ranking from implicit feedback K Damak, S Khenissi, O Nasraoui Proceedings of the 15th ACM Conference on Recommender Systems, 321-331, 2021 | 22 | 2021 |
| Sequence-based explainable hybrid song recommendation K Damak, O Nasraoui, WS Sanders Frontiers in big Data 4, 693494, 2021 | 10 | 2021 |
| Debiasing the Cloze Task in Sequential Recommendation with Bidirectional Transformers K Damak, S Khenissi, O Nasraoui Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 8 | 2022 |
| SeER: an explainable deep learning MIDI-based hybrid song recommender system K Damak, O Nasraoui arXiv preprint arXiv:1907.01640, 2019 | 6 | 2019 |
| A Data Science Approach to Flagging Non-Retention in Engineering Enrollment Data M Boujelbene, MK Damak 2020 ASEE Virtual Annual Conference Content Access, 2020 | 1 | 2020 |
| Robot failure mode prediction with deep learning sequence models K Damak, M Boujelbene, C Acun, A Alvanpour, SK Das, DO Popa, ... Neural Computing and Applications, 1-12, 2024 | | 2024 |
| A framework for unbiased explainable pairwise ranking for recommendation K Damak, S Khenissi, O Nasraoui Software Impacts 11, 100208, 2022 | | 2022 |
| New accurate, explainable, and unbiased machine learning models for recommendation with implicit feedback. K Damak | | 2022 |
| An explainable sequence-based deep learning predictor with applications to song recommendation and text classification. K Damak | | 2019 |
